Lead AI Engineer

Summary: You will design, develop, and deploy innovative AI/ML solutions for manufacturing and industrial products. A strong hands-on engineering approach, technical mentorship, and the ability to take projects from conception to deployment are expected. Cross-functional collaboration is key, but the position carries less strategic oversight and talent development responsibility than a Principal role. Responsibilities: - Architect and implement AI/ML models for automation, predictive analytics, and process optimization in manufacturing. - Develop and maintain scalable data and ML pipelines execute on end-to-end AI solution lifecycles (from data processing to model deployment and monitoring). - Collaborate with product, engineering, and operations teams to design and integrate AI features into digital products. - Apply Generative AI or LLMs for use cases in simulation, generative design, digital documentation, and intelligent operator assistance. - Champion best MLOps practices, code quality, and testing for robust AI deployments. - Mentor junior engineers and data scientists on technical best practices. - Remain current with industry and AI advancements, and quickly adapt solutions to evolving needs. Requirements: - 5&ndash10 years of hands-on AI/ML engineering (preferably in manufacturing, SaaS, or product companies). Required Skills: - Proven ability in Machine Learning, Deep Learning, Natural Language Processing (NLP), and/or Generative AI (LLMs, RAG, transformers). - Experience deploying models with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc. - Strong programming skills in Python familiarity with other languages or tools (Java, Go, Scala, Docker, K8s) is a plus. - Experience with model training, fine-tuning, prompt engineering, and use of vector databases. - Familiarity with cloud services (AWS/GCP/Azure) for model deployment. - Experience with MLOps, CI/CD for ML, and version control (Git). - Excellent communication and ability to work in a cross-functional team. Preferred Skills: - Experience with or exposure to digital twin tech in manufacturing (e.g., Nvidia Omniverse, Siemens, PTC) participate in integration/consumption rather than full-scale digital twin architecture. - Knowledge of manufacturing data/standards (IoT, PLCs, MES/ERP connectivity). - Masters in relevant fields, open-source contributions, or research publications. #AditiConsulting # 26-04480 Skills: Git, Machine Learning, Docker, Scala, Deep Learning, Tensorflow, Gcp, Pytorch, MLops, Transformers, Go, Azure, Java, Aws, Python Experience: 5.00-10.00 Years